2D Euclidean distance transform algorithms: A comparative survey

  • Authors:
  • Ricardo Fabbri;Luciano Da F. Costa;Julio C. Torelli;Odemir M. Bruno

  • Affiliations:
  • Brown University, Providence, RI;Instituto de Física de São Carlos, USP, SP, Brazil;Instituto de Ciências Matemáticas e de Computação, USP, SP, Brazil;Instituto de Ciências Matemáticas e de Computação, USP, SP, Brazil

  • Venue:
  • ACM Computing Surveys (CSUR)
  • Year:
  • 2008

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Abstract

The distance transform (DT) is a general operator forming the basis of many methods in computer vision and geometry, with great potential for practical applications. However, all the optimal algorithms for the computation of the exact Euclidean DT (EDT) were proposed only since the 1990s. In this work, state-of-the-art sequential 2D EDT algorithms are reviewed and compared, in an effort to reach more solid conclusions regarding their differences in speed and their exactness. Six of the best algorithms were fully implemented and compared in practice.